Machine Learning Engineer

You are a passionate and skilled Machine Learning Engineer who will be joining our team. Your role will involve designing, building, and deploying robust ML models to solve real-world problems. You will work with large and complex datasets to extract insights and optimize performance. Collaboration with data engineers, product managers, and developers to integrate ML models into production will be a key aspect of your responsibilities. It will be essential for you to continuously improve model performance and reliability through experimentation and tuning. Staying up-to-date with the latest advancements in ML/AI and applying them where relevant is also expected from you. To excel in this role, you should possess a strong knowledge of machine learning algorithms, data preprocessing, and model evaluation. Hands-on experience with Python and ML libraries like scikit-learn, TensorFlow, PyTorch, etc., will be crucial. A solid understanding of statistics, probability, and optimization techniques is required. Previous experience working with real-world datasets, including cleaning, transforming, and feature engineering, will be beneficial. Your ability to work independently, take ownership of projects, and your genuine passion for sports, especially fantasy sports, will set you apart. It would be advantageous if you have experience with recommendation systems, predictive modeling, or NLP. Familiarity with deployment frameworks and cloud platforms such as AWS, GCP, etc., will be a plus. Contributions to open-source or ML competitions like Kaggle are also desirable. This is a full-time position. As part of the benefits, internet reimbursement will be provided. The job follows a day shift schedule. As part of the application process, kindly provide the following information: - What is your current CTC - What is your expected CTC - Are you comfortable relocating to Indore, MP - Have you worked on any projects or products related to the fantasy sports domain or sports tech If yes, for how many years ,